Life Science Knowledge Discovery

BioAsk: intelligent biomedical knowledge discovery platform

Search biomedical literature, patents, and clinical-trial knowledge using entity extraction, relationship discovery, and visual, structured exploration.

Knowledge Graph Preview

p53
MDM2
DNA repair
Apoptosis
Cancer
EntityTP53 tumor suppressor
Relationshipp53 regulates apoptosis
SourceLiterature / patents / trials

Knowledge Sources

Search across biomedical repositories

The original BioAsk community edition covered Medline abstracts, patents, and clinical trials — BioAsk searches all three from one place.

Literature

Medline abstracts

Scientific publication abstracts for biomedical discovery.

Innovation

Patents

Patent-linked innovation, technology, molecules, and methods.

Clinical

Clinical trials

Trial-related biomedical and therapeutic knowledge signals.

Scientific Publications Explorer
Live · PubMed · Europe PMC · Springer · Wiley · DOAJ · bioRxiv
Sources: PubMed Europe PMC Springer Wiley DOAJ bioRxiv
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Gene Report

BRCA1

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Bases & Alias
Fonction
Variants
Structure
Expression
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RCSB PDB Structure Summary

23OI
Structure
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Macromolecule Content

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PDB DOI: -
Classification: -
Organism(s): -
Expression System: -
Method: -
Resolution: -
Deposited / Released: -
Macromolecules

Core Features

Designed for biomedical discovery

BioAsk combines search, text mining, categorization, entity recognition, and visualization into one research interface.

Biomedical search

Search life-science content across biomedical literature, patent records, and clinical-trial information.

Bio-entity detection

Identify genes, proteins, diseases, pathways, and organisms inside unstructured biomedical text.

Entity relationships

Discover hidden associations between biological entities that keyword search alone would miss.

Visualization

Explore relationships through graphs, clusters, and structured views that clarify complex results.

Search Experience

From keywords to structured knowledge

Instead of only listing documents, BioAsk organizes results by themes, entities, facts, and relationships — moving researchers from search results to usable biological insight.

  • Extract biological concepts from text
  • Group results by themes and entities
  • Visualize relationships between terms
  • Annotate and refine discoveries
Entities
Relations
Themes

Detected Entities

TP53MDM2 apoptosisDNA damage breast cancercell cycle

Detected Relations

TP53 → regulates → apoptosis. MDM2 → inhibits → TP53. DNA damage → activates → TP53.

Detected Themes

Tumor suppression, cell-cycle arrest, DNA-damage response, hereditary breast cancer risk.

Workflow

How BioAsk works

1

Ask a biological question

Start with a keyword, gene, disease, pathway, molecule, or research question.

2

Search biomedical repositories

Retrieve relevant records from literature, patents, and clinical knowledge sources.

3

Extract entities and facts

Detect biological entities, concepts, and relationships from unstructured text.

4

Explore visual knowledge

Use categorized results and graph-style visualization to find research connections.

Example Queries

Questions researchers can ask

What genes are associated with Alzheimer's disease?
Which proteins interact with EGFR?
What pathways are involved in apoptosis?
Which patents mention monoclonal antibodies against HER2?
What clinical trials target inflammatory cytokines?
Which biomarkers are linked to colorectal cancer?

Rebuild BioAsk as a modern biomedical discovery portal

A clean homepage for search, research navigation, biomedical knowledge discovery, and AI-assisted life-science exploration.

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